Editorial: Artificial Intelligence (AI), Digital Image Analysis, and the Future of Cancer Diagnosis and Prognosis.


Journal

Medical science monitor : international medical journal of experimental and clinical research
ISSN: 1643-3750
Titre abrégé: Med Sci Monit
Pays: United States
ID NLM: 9609063

Informations de publication

Date de publication:
01 Nov 2024
Historique:
medline: 1 11 2024
pubmed: 1 11 2024
entrez: 1 11 2024
Statut: epublish

Résumé

On October 8 2024, the Royal Swedish Academy of Sciences announced the 2024 Nobel Prize in Physics was awarded to Hopfield and Hinton for their foundation research on machine learning with artificial neural networks, which resulted in the current applications for artificial intelligence (AI). Digital diagnostic histopathology combines image capture with image analysis and uses digital tools to collect, analyze, and share diagnostic information. An increase in chronic diseases, diagnostic departmental workloads, and diagnostic tests to support targeted therapy in cancer patients have driven the use and development of image analysis systems, and several medical device companies have recently developed whole-slide scanning devices. In April 2017, the US Food and Drug Administration (FDA) permitted marketing authorization for the first whole slide imaging (WSI) system. During 2024, large-scale studies from several cancer centers have shown the potential for diagnostic reporting for real-world data and whole-slide modeling to develop validated diagnostic AI algorithms. This editorial discusses why recent advances and applications in AI and digital image analysis may have an important future role in cancer diagnosis and prognosis.

Identifiants

pubmed: 39482925
pii: 947038
doi: 10.12659/MSM.947038
doi:

Types de publication

Editorial

Langues

eng

Sous-ensembles de citation

IM

Pagination

e947038

Auteurs

Dinah V Parums (DV)

Science Editor, Medical Science Monitor, International Scientific Information, Inc., Melville, NY, USA.

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Classifications MeSH